{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Objective\n",
    "* 20181226: \n",
    "    * Predict stock price in next day using linear regression\n",
    "    * Given prices for the last N days, we train a model, and predict for day N+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import math\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import time\n",
    "\n",
    "from datetime import date, datetime, time, timedelta\n",
    "from matplotlib import pyplot as plt\n",
    "from pylab import rcParams\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import r2_score\n",
    "from tqdm import tqdm_notebook\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "#### Input params ##################\n",
    "stk_path = \"./data/VTI.csv\"\n",
    "test_size = 0.2                 # proportion of dataset to be used as test set\n",
    "cv_size = 0.2                   # proportion of dataset to be used as cross-validation set\n",
    "Nmax = 30                       # for feature at day t, we use lags from t-1, t-2, ..., t-N as features\n",
    "                                # Nmax is the maximum N we are going to test\n",
    "fontsize = 14\n",
    "ticklabelsize = 14\n",
    "####################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Common functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_preds_lin_reg(df, target_col, N, pred_min, offset):\n",
    "    \"\"\"\n",
    "    Given a dataframe, get prediction at timestep t using values from t-1, t-2, ..., t-N.\n",
    "    Inputs\n",
    "        df         : dataframe with the values you want to predict. Can be of any length.\n",
    "        target_col : name of the column you want to predict e.g. 'adj_close'\n",
    "        N          : get prediction at timestep t using values from t-1, t-2, ..., t-N\n",
    "        pred_min   : all predictions should be >= pred_min\n",
    "        offset     : for df we only do predictions for df[offset:]. e.g. offset can be size of training set\n",
    "    Outputs\n",
    "        pred_list  : the predictions for target_col. np.array of length len(df)-offset.\n",
    "    \"\"\"\n",
    "    # Create linear regression object\n",
    "    regr = LinearRegression(fit_intercept=True)\n",
    "\n",
    "    pred_list = []\n",
    "\n",
    "    for i in range(offset, len(df['adj_close'])):\n",
    "        X_train = np.array(range(len(df['adj_close'][i-N:i]))) # e.g. [0 1 2 3 4]\n",
    "        y_train = np.array(df['adj_close'][i-N:i]) # e.g. [2944 3088 3226 3335 3436]\n",
    "        X_train = X_train.reshape(-1, 1)     # e.g X_train = \n",
    "                                             # [[0]\n",
    "                                             #  [1]\n",
    "                                             #  [2]\n",
    "                                             #  [3]\n",
    "                                             #  [4]]\n",
    "        # X_train = np.c_[np.ones(N), X_train]              # add a column\n",
    "        y_train = y_train.reshape(-1, 1)\n",
    "    #     print X_train.shape\n",
    "    #     print y_train.shape\n",
    "    #     print 'X_train = \\n' + str(X_train)\n",
    "    #     print 'y_train = \\n' + str(y_train)\n",
    "        regr.fit(X_train, y_train)            # Train the model\n",
    "        pred = regr.predict(N)\n",
    "    \n",
    "        pred_list.append(pred[0][0])  # Predict the footfall using the model\n",
    "    \n",
    "    # If the values are < pred_min, set it to be pred_min\n",
    "    pred_list = np.array(pred_list)\n",
    "    pred_list[pred_list < pred_min] = pred_min\n",
    "        \n",
    "    return pred_list\n",
    "\n",
    "def get_mape(y_true, y_pred): \n",
    "    \"\"\"\n",
    "    Compute mean absolute percentage error (MAPE)\n",
    "    \"\"\"\n",
    "    y_true, y_pred = np.array(y_true), np.array(y_pred)\n",
    "    return np.mean(np.abs((y_true - y_pred) / y_true)) * 100\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>adj_close</th>\n",
       "      <th>volume</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-11-25</td>\n",
       "      <td>107.510002</td>\n",
       "      <td>107.660004</td>\n",
       "      <td>107.250000</td>\n",
       "      <td>107.470001</td>\n",
       "      <td>101.497200</td>\n",
       "      <td>1820300</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-11-27</td>\n",
       "      <td>107.589996</td>\n",
       "      <td>107.760002</td>\n",
       "      <td>107.220001</td>\n",
       "      <td>107.629997</td>\n",
       "      <td>101.648300</td>\n",
       "      <td>552400</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-11-30</td>\n",
       "      <td>107.779999</td>\n",
       "      <td>107.849998</td>\n",
       "      <td>107.110001</td>\n",
       "      <td>107.169998</td>\n",
       "      <td>101.213867</td>\n",
       "      <td>3618100</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>107.589996</td>\n",
       "      <td>108.209999</td>\n",
       "      <td>107.370003</td>\n",
       "      <td>108.180000</td>\n",
       "      <td>102.167740</td>\n",
       "      <td>2443600</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-12-02</td>\n",
       "      <td>108.099998</td>\n",
       "      <td>108.269997</td>\n",
       "      <td>106.879997</td>\n",
       "      <td>107.050003</td>\n",
       "      <td>101.100533</td>\n",
       "      <td>2937200</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015-12-03</td>\n",
       "      <td>107.290001</td>\n",
       "      <td>107.480003</td>\n",
       "      <td>105.059998</td>\n",
       "      <td>105.449997</td>\n",
       "      <td>99.589470</td>\n",
       "      <td>3345600</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2015-12-04</td>\n",
       "      <td>105.809998</td>\n",
       "      <td>107.540001</td>\n",
       "      <td>105.620003</td>\n",
       "      <td>107.389999</td>\n",
       "      <td>101.421646</td>\n",
       "      <td>4520000</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2015-12-07</td>\n",
       "      <td>107.230003</td>\n",
       "      <td>107.269997</td>\n",
       "      <td>106.059998</td>\n",
       "      <td>106.550003</td>\n",
       "      <td>100.628342</td>\n",
       "      <td>3000500</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2015-12-08</td>\n",
       "      <td>105.940002</td>\n",
       "      <td>106.400002</td>\n",
       "      <td>105.269997</td>\n",
       "      <td>105.910004</td>\n",
       "      <td>100.023895</td>\n",
       "      <td>3149600</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2015-12-09</td>\n",
       "      <td>105.550003</td>\n",
       "      <td>106.750000</td>\n",
       "      <td>104.480003</td>\n",
       "      <td>105.000000</td>\n",
       "      <td>99.164467</td>\n",
       "      <td>4179800</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date        open        high         low       close   adj_close  \\\n",
       "0 2015-11-25  107.510002  107.660004  107.250000  107.470001  101.497200   \n",
       "1 2015-11-27  107.589996  107.760002  107.220001  107.629997  101.648300   \n",
       "2 2015-11-30  107.779999  107.849998  107.110001  107.169998  101.213867   \n",
       "3 2015-12-01  107.589996  108.209999  107.370003  108.180000  102.167740   \n",
       "4 2015-12-02  108.099998  108.269997  106.879997  107.050003  101.100533   \n",
       "5 2015-12-03  107.290001  107.480003  105.059998  105.449997   99.589470   \n",
       "6 2015-12-04  105.809998  107.540001  105.620003  107.389999  101.421646   \n",
       "7 2015-12-07  107.230003  107.269997  106.059998  106.550003  100.628342   \n",
       "8 2015-12-08  105.940002  106.400002  105.269997  105.910004  100.023895   \n",
       "9 2015-12-09  105.550003  106.750000  104.480003  105.000000   99.164467   \n",
       "\n",
       "    volume  month  \n",
       "0  1820300     11  \n",
       "1   552400     11  \n",
       "2  3618100     11  \n",
       "3  2443600     12  \n",
       "4  2937200     12  \n",
       "5  3345600     12  \n",
       "6  4520000     12  \n",
       "7  3000500     12  \n",
       "8  3149600     12  \n",
       "9  4179800     12  "
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(stk_path, sep = \",\")\n",
    "\n",
    "# Convert Date column to datetime\n",
    "df.loc[:, 'Date'] = pd.to_datetime(df['Date'],format='%Y-%m-%d')\n",
    "\n",
    "# Change all column headings to be lower case, and remove spacing\n",
    "df.columns = [str(x).lower().replace(' ', '_') for x in df.columns]\n",
    "\n",
    "# Get month of each sample\n",
    "df['month'] = df['date'].dt.month\n",
    "\n",
    "# Sort by datetime\n",
    "df.sort_values(by='date', inplace=True, ascending=True)\n",
    "\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1a2dca58>"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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zyTVjWLNBg6rvi4iQ3lTHHtVgwOCMiIiCRv/+ErykpUlvWVGRzNG67DLJhD96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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a19e298d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "\n",
    "ax = df.plot(x='date', y='adj_close', style='b-', grid=True)\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Split into train, dev and test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num_train = 453\n",
      "num_cv = 151\n",
      "num_test = 151\n",
      "train.shape = (453, 8)\n",
      "cv.shape = (151, 8)\n",
      "train_cv.shape = (604, 8)\n",
      "test.shape = (151, 8)\n"
     ]
    }
   ],
   "source": [
    "# Get sizes of each of the datasets\n",
    "num_cv = int(cv_size*len(df))\n",
    "num_test = int(test_size*len(df))\n",
    "num_train = len(df) - num_cv - num_test\n",
    "print(\"num_train = \" + str(num_train))\n",
    "print(\"num_cv = \" + str(num_cv))\n",
    "print(\"num_test = \" + str(num_test))\n",
    "\n",
    "# Split into train, cv, and test\n",
    "train = df[:num_train]\n",
    "cv = df[num_train:num_train+num_cv]\n",
    "train_cv = df[:num_train+num_cv]\n",
    "test = df[num_train+num_cv:]\n",
    "print(\"train.shape = \" + str(train.shape))\n",
    "print(\"cv.shape = \" + str(cv.shape))\n",
    "print(\"train_cv.shape = \" + str(train_cv.shape))\n",
    "print(\"test.shape = \" + str(test.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1a26c080>"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2b/8/oHH3Y3Pi4zPqri1r8brq6nwgvklyVlm5nuTkAYHu0c5Izlbuceu3Xzz6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\nODHpOAoQ33/VvbYUHw3EZ3XLjf/yfg44DB8JNzw63rZY5W1BnGPxv1i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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a19febb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "\n",
    "ax = train.plot(x='date', y='adj_close', style='b-', grid=True)\n",
    "ax = cv.plot(x='date', y='adj_close', style='y-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='adj_close', style='g-', grid=True, ax=ax)\n",
    "ax.legend(['train', 'dev', 'test'])\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predict using Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yibin/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  import sys\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = [1.1982002858601004, 1.7095123283755445, 1.6223619801087072, 1.4366144520084778, 1.362231982616558, 1.383474067943486, 1.4368793143782175, 1.4754155083541898, 1.5635060458761834, 1.6596574531936923, 1.7461971163055439, 1.8358579130668853, 1.918790804577929, 1.99757093053822, 2.065489759563188, 2.1260803213133252, 2.1769031692909406, 2.2118049794321077, 2.239495141907283, 2.2711862366946516, 2.308445275776052, 2.346141216648513, 2.3836648601150077, 2.422248786281851, 2.4636508932290213, 2.5082823773226726, 2.5482293954205297, 2.581182656095775, 2.6124103233400024, 2.6370488198768443]\n",
      "R2 = [0.9365823483250227, 0.8709090512123931, 0.8837355774902559, 0.9088342350077783, 0.9180302777526336, 0.9154539417158228, 0.9088006162363634, 0.9038431989583758, 0.8920182284016229, 0.8783286743800709, 0.8653092249716993, 0.85112236879997, 0.8373677855225893, 0.8237391998675757, 0.8115494493354859, 0.8003309948773554, 0.7906709310387531, 0.7839048690670168, 0.7784602976432697, 0.772145917678097, 0.7646086575541071, 0.7568582059106395, 0.749018502113711, 0.7408275629664495, 0.7318920743285626, 0.7220900012034247, 0.7131674981019763, 0.7057009941342747, 0.6985369414235654, 0.6928237328172369]\n",
      "MAPE = [0.577172367136675, 0.7993734607852511, 0.7761128464506516, 0.7066780093520814, 0.7072769202705996, 0.7034030038324438, 0.7278263170138026, 0.7356319397609785, 0.7727732509244185, 0.8081992183612657, 0.833631451344786, 0.861331631837276, 0.8993785985076994, 0.9396395765127592, 0.9770683575536612, 1.0049841076526103, 1.0295931771731295, 1.0350629570442347, 1.042022809362379, 1.0475380699815606, 1.0582243187311855, 1.0841831635848347, 1.1147228218359972, 1.1460141708300062, 1.1752390430362545, 1.2018752249027198, 1.221317438073218, 1.2327899499581192, 1.2426793058177144, 1.2493455659411812]\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>adj_close</th>\n",
       "      <th>volume</th>\n",
       "      <th>month</th>\n",
       "      <th>est_N1</th>\n",
       "      <th>est_N2</th>\n",
       "      <th>...</th>\n",
       "      <th>est_N21</th>\n",
       "      <th>est_N22</th>\n",
       "      <th>est_N23</th>\n",
       "      <th>est_N24</th>\n",
       "      <th>est_N25</th>\n",
       "      <th>est_N26</th>\n",
       "      <th>est_N27</th>\n",
       "      <th>est_N28</th>\n",
       "      <th>est_N29</th>\n",
       "      <th>est_N30</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2017-09-14</td>\n",
       "      <td>128.229996</td>\n",
       "      <td>128.479996</td>\n",
       "      <td>128.070007</td>\n",
       "      <td>128.360001</td>\n",
       "      <td>125.536995</td>\n",
       "      <td>1493200</td>\n",
       "      <td>9</td>\n",
       "      <td>125.576111</td>\n",
       "      <td>125.634781</td>\n",
       "      <td>...</td>\n",
       "      <td>124.972034</td>\n",
       "      <td>124.808824</td>\n",
       "      <td>124.777203</td>\n",
       "      <td>124.760472</td>\n",
       "      <td>124.591849</td>\n",
       "      <td>124.435939</td>\n",
       "      <td>124.276145</td>\n",
       "      <td>124.156451</td>\n",
       "      <td>124.071092</td>\n",
       "      <td>123.977512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2017-09-15</td>\n",
       "      <td>128.309998</td>\n",
       "      <td>128.619995</td>\n",
       "      <td>128.199997</td>\n",
       "      <td>128.600006</td>\n",
       "      <td>125.771729</td>\n",
       "      <td>1531300</td>\n",
       "      <td>9</td>\n",
       "      <td>125.536995</td>\n",
       "      <td>125.497879</td>\n",
       "      <td>...</td>\n",
       "      <td>125.393974</td>\n",
       "      <td>125.221366</td>\n",
       "      <td>125.060786</td>\n",
       "      <td>125.025206</td>\n",
       "      <td>125.004079</td>\n",
       "      <td>124.837163</td>\n",
       "      <td>124.681643</td>\n",
       "      <td>124.521730</td>\n",
       "      <td>124.399952</td>\n",
       "      <td>124.311090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455</th>\n",
       "      <td>2017-09-18</td>\n",
       "      <td>128.850006</td>\n",
       "      <td>129.100006</td>\n",
       "      <td>128.690002</td>\n",
       "      <td>128.910004</td>\n",
       "      <td>126.074898</td>\n",
       "      <td>1792300</td>\n",
       "      <td>9</td>\n",
       "      <td>125.771729</td>\n",
       "      <td>126.006463</td>\n",
       "      <td>...</td>\n",
       "      <td>125.855084</td>\n",
       "      <td>125.638482</td>\n",
       "      <td>125.470393</td>\n",
       "      <td>125.312516</td>\n",
       "      <td>125.273619</td>\n",
       "      <td>125.248711</td>\n",
       "      <td>125.083603</td>\n",
       "      <td>124.928692</td>\n",
       "      <td>124.768923</td>\n",
       "      <td>124.645458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>2017-09-19</td>\n",
       "      <td>129.059998</td>\n",
       "      <td>129.100006</td>\n",
       "      <td>128.850006</td>\n",
       "      <td>128.970001</td>\n",
       "      <td>126.133591</td>\n",
       "      <td>1241700</td>\n",
       "      <td>9</td>\n",
       "      <td>126.074898</td>\n",
       "      <td>126.378067</td>\n",
       "      <td>...</td>\n",
       "      <td>126.128319</td>\n",
       "      <td>126.103607</td>\n",
       "      <td>125.894686</td>\n",
       "      <td>125.730437</td>\n",
       "      <td>125.574845</td>\n",
       "      <td>125.532753</td>\n",
       "      <td>125.504201</td>\n",
       "      <td>125.340619</td>\n",
       "      <td>125.186166</td>\n",
       "      <td>125.026453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>2017-09-20</td>\n",
       "      <td>129.100006</td>\n",
       "      <td>129.210007</td>\n",
       "      <td>128.600006</td>\n",
       "      <td>129.179993</td>\n",
       "      <td>126.338959</td>\n",
       "      <td>1729200</td>\n",
       "      <td>9</td>\n",
       "      <td>126.133591</td>\n",
       "      <td>126.192284</td>\n",
       "      <td>...</td>\n",
       "      <td>126.327509</td>\n",
       "      <td>126.343665</td>\n",
       "      <td>126.319986</td>\n",
       "      <td>126.119552</td>\n",
       "      <td>125.960280</td>\n",
       "      <td>125.808192</td>\n",
       "      <td>125.764475</td>\n",
       "      <td>125.733764</td>\n",
       "      <td>125.572721</td>\n",
       "      <td>125.419771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          date        open        high         low       close   adj_close  \\\n",
       "453 2017-09-14  128.229996  128.479996  128.070007  128.360001  125.536995   \n",
       "454 2017-09-15  128.309998  128.619995  128.199997  128.600006  125.771729   \n",
       "455 2017-09-18  128.850006  129.100006  128.690002  128.910004  126.074898   \n",
       "456 2017-09-19  129.059998  129.100006  128.850006  128.970001  126.133591   \n",
       "457 2017-09-20  129.100006  129.210007  128.600006  129.179993  126.338959   \n",
       "\n",
       "      volume  month      est_N1      est_N2     ...         est_N21  \\\n",
       "453  1493200      9  125.576111  125.634781     ...      124.972034   \n",
       "454  1531300      9  125.536995  125.497879     ...      125.393974   \n",
       "455  1792300      9  125.771729  126.006463     ...      125.855084   \n",
       "456  1241700      9  126.074898  126.378067     ...      126.128319   \n",
       "457  1729200      9  126.133591  126.192284     ...      126.327509   \n",
       "\n",
       "        est_N22     est_N23     est_N24     est_N25     est_N26     est_N27  \\\n",
       "453  124.808824  124.777203  124.760472  124.591849  124.435939  124.276145   \n",
       "454  125.221366  125.060786  125.025206  125.004079  124.837163  124.681643   \n",
       "455  125.638482  125.470393  125.312516  125.273619  125.248711  125.083603   \n",
       "456  126.103607  125.894686  125.730437  125.574845  125.532753  125.504201   \n",
       "457  126.343665  126.319986  126.119552  125.960280  125.808192  125.764475   \n",
       "\n",
       "        est_N28     est_N29     est_N30  \n",
       "453  124.156451  124.071092  123.977512  \n",
       "454  124.521730  124.399952  124.311090  \n",
       "455  124.928692  124.768923  124.645458  \n",
       "456  125.340619  125.186166  125.026453  \n",
       "457  125.733764  125.572721  125.419771  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RMSE = []\n",
    "R2 = []\n",
    "mape = []\n",
    "for N in range(1, Nmax+1): # N is no. of samples to use to predict the next value\n",
    "    est_list = get_preds_lin_reg(train_cv, 'adj_close', N, 0, num_train)\n",
    "    \n",
    "    cv['est' + '_N' + str(N)] = est_list\n",
    "    RMSE.append(math.sqrt(mean_squared_error(est_list, cv['adj_close'])))\n",
    "    R2.append(r2_score(cv['adj_close'], est_list))\n",
    "    mape.append(get_mape(cv['adj_close'], est_list))\n",
    "print('RMSE = ' + str(RMSE))\n",
    "print('R2 = ' + str(R2))\n",
    "print('MAPE = ' + str(mape))\n",
    "cv.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 30)"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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YWbaJtADpaYGjesD8TTuZX7HFUqMmY6mRJElSk6mpreOvb67k508vpHT1Vjq0S+OMYb15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\n9v8BN40ea+hSQiAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1d59cfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot RMSE versus N\n",
    "matplotlib.rcParams.update({'font.size': 14})\n",
    "plt.figure(figsize=(12, 8), dpi=80)\n",
    "plt.plot(range(1, Nmax+1), RMSE, 'x-')\n",
    "plt.grid()\n",
    "plt.xlabel('N')\n",
    "plt.ylabel('RMSE')\n",
    "plt.xlim([2, 30])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lowest RMSE is achieved with N=1, followed by N=5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1bf7bcf8>"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qIpQ+XtuaN4zQ/Re308I/XqTerRuquNSrMq9VXc4FAADwcY6UHGPMGcaYT4wxBcaYPcaY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\nAAAA+AolBwAAAICvUHIAAAAA+Mr/A8zHUkxyIJprAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1bccba90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot R2 versus N. Note for R2 larger better. \n",
    "matplotlib.rcParams.update({'font.size': 14})\n",
    "plt.figure(figsize=(12, 8), dpi=80)\n",
    "plt.plot(range(1, Nmax+1), R2, 'x-')\n",
    "plt.grid()\n",
    "plt.xlabel('N')\n",
    "plt.ylabel('R2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1b0f64e0>"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LWqt3Fm/RH97PU5mnRiOGdNKjl/VWZBjf/gDAH/C3MQAgIO2sqNJv31mmD5cX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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1b0e64e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot MAPE versus N. Note for MAPE smaller better. \n",
    "plt.figure(figsize=(12, 8), dpi=80)\n",
    "plt.plot(range(1, Nmax+1), mape, 'x-')\n",
    "plt.grid()\n",
    "plt.xlabel('N')\n",
    "plt.ylabel('MAPE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set optimum N\n",
    "N_opt = 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot predictions for a specific day. For checking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gdrtxu90AxMTEEBsby4YNGxg4cCCpqakMHDiQQYMGcc011xAaGlrisYwfP564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\nZOiSJEmSpCr6/2ixUmkTRezfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1c9105f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Specify the day you are interested in\n",
    "day = pd.Timestamp(date(2017, 10, 31))\n",
    "\n",
    "# Specify the maximum N you want to plot (If Nmax2 is too large it gets very cluttered) \n",
    "Nmax2 = 5\n",
    "\n",
    "df_temp = cv[cv['date'] <= day]\n",
    "plt.figure(figsize=(12, 8), dpi=80)\n",
    "plt.plot(range(1,Nmax2+2), df_temp[-Nmax2-1:]['adj_close'], 'bx-')\n",
    "plt.plot(Nmax2+1, df_temp[-1:]['adj_close'], 'ys-')\n",
    "legend_list = ['adj_close', 'actual_value']\n",
    "\n",
    "# Plot the linear regression lines and the predictions\n",
    "color_list = ['r', 'g', 'k', 'y', 'm', 'c', '0.75']\n",
    "marker_list = ['x', 'x', 'x', 'x', 'x', 'x', 'x']\n",
    "regr = LinearRegression(fit_intercept=True) # Create linear regression object\n",
    "for N in range(5, Nmax2+1):\n",
    "    # Plot the linear regression lines\n",
    "    X_train = np.array(range(len(df_temp['adj_close'][-N-1:-1]))) # e.g. [0 1 2 3 4]\n",
    "    y_train = np.array(df_temp['adj_close'][-N-1:-1]) # e.g. [2944 3088 3226 3335 3436]\n",
    "    X_train = X_train.reshape(-1, 1)     \n",
    "    y_train = y_train.reshape(-1, 1)\n",
    "    regr.fit(X_train, y_train)            # Train the model\n",
    "    y_est = regr.predict(X_train)         # Get linear regression line\n",
    "    plt.plot(range(Nmax2+1-N,Nmax2+2), \n",
    "             np.concatenate((y_est, np.array(df_temp['est_N'+str(N)][-1:]).reshape(-1,1))),\n",
    "             color=color_list[N%len(color_list)], \n",
    "             marker=marker_list[N%len(marker_list)])\n",
    "    legend_list.append('est_N'+str(N)+'_lr')\n",
    "    \n",
    "    # Plot the predictions\n",
    "    plt.plot(Nmax2+1, \n",
    "             df_temp['est_N'+str(N)][-1:], \n",
    "             color=color_list[N%len(color_list)], \n",
    "             marker='o')\n",
    "    legend_list.append('est_N'+str(N))\n",
    "    \n",
    "\n",
    "plt.grid()\n",
    "plt.xlabel('timestep')\n",
    "plt.ylabel('USD')\n",
    "plt.legend(legend_list, bbox_to_anchor=(1.05, 1))\n",
    "matplotlib.rcParams.update({'font.size': fontsize})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot predictions on dev set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1b8319b0>"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FWkXLw30frrVsVEAU//ntP1yyXkIIwYrtK4DWtfsD4BoXp9eWb9EWYAzAS+fl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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1a66d3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "\n",
    "ax = train.plot(x='date', y='adj_close', style='b-', grid=True)\n",
    "ax = cv.plot(x='date', y='adj_close', style='y-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='adj_close', style='g-', grid=True, ax=ax)\n",
    "ax = cv.plot(x='date', y='est_N1', style='r-', grid=True, ax=ax)\n",
    "ax = cv.plot(x='date', y='est_N5', style='m-', grid=True, ax=ax)\n",
    "ax.legend(['train', 'dev', 'test', 'predictions with N=1', 'predictions with N=5'])\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1bcd9978>"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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530hBch7WP/LJTighc0cA2Ue7oJUYIBdcbPl4qsN42g5gzk/BnPknLnk7wGrV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omysreJjT2c+PhjaapsYu6Jc6lbWcfQz4YSPzIUTr0aamrg8cfhhhtw35rFph2jdlF/+jz/Pcvj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\nY4w50BhzQFeXo6vpc3P3UJjbA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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1bcebe80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "\n",
    "ax = train.plot(x='date', y='adj_close', style='bx-', grid=True)\n",
    "ax = cv.plot(x='date', y='adj_close', style='yx-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='adj_close', style='gx-', grid=True, ax=ax)\n",
    "ax = cv.plot(x='date', y='est_N1', style='rx-', grid=True, ax=ax)\n",
    "ax = cv.plot(x='date', y='est_N5', style='mx-', grid=True, ax=ax)\n",
    "ax.legend(['train', 'dev', 'test', 'predictions with N=1', 'predictions with N=5'])\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")\n",
    "ax.set_xlim([date(2017, 11, 1), date(2017, 12, 30)])\n",
    "ax.set_ylim([127, 137])\n",
    "ax.set_title('Zoom in to dev set')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE = 1.420\n",
      "R2 = 0.900\n",
      "MAPE = 0.707%\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yibin/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>adj_close</th>\n",
       "      <th>volume</th>\n",
       "      <th>month</th>\n",
       "      <th>est_N5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>604</th>\n",
       "      <td>2018-04-23</td>\n",
       "      <td>137.779999</td>\n",
       "      <td>138.160004</td>\n",
       "      <td>136.809998</td>\n",
       "      <td>137.449997</td>\n",
       "      <td>136.219604</td>\n",
       "      <td>2033700</td>\n",
       "      <td>4</td>\n",
       "      <td>136.930182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>2018-04-24</td>\n",
       "      <td>138.100006</td>\n",
       "      <td>138.190002</td>\n",
       "      <td>134.860001</td>\n",
       "      <td>135.800003</td>\n",
       "      <td>134.584366</td>\n",
       "      <td>3053500</td>\n",
       "      <td>4</td>\n",
       "      <td>135.601195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>2018-04-25</td>\n",
       "      <td>135.770004</td>\n",
       "      <td>136.250000</td>\n",
       "      <td>134.610001</td>\n",
       "      <td>135.949997</td>\n",
       "      <td>134.733032</td>\n",
       "      <td>2275400</td>\n",
       "      <td>4</td>\n",
       "      <td>134.050198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>607</th>\n",
       "      <td>2018-04-26</td>\n",
       "      <td>136.520004</td>\n",
       "      <td>137.679993</td>\n",
       "      <td>136.250000</td>\n",
       "      <td>137.240005</td>\n",
       "      <td>136.011490</td>\n",
       "      <td>1284600</td>\n",
       "      <td>4</td>\n",
       "      <td>133.751889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>608</th>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>137.539993</td>\n",
       "      <td>137.740005</td>\n",
       "      <td>136.800003</td>\n",
       "      <td>137.330002</td>\n",
       "      <td>136.100677</td>\n",
       "      <td>1133600</td>\n",
       "      <td>4</td>\n",
       "      <td>134.962961</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date        open        high         low       close   adj_close  \\\n",
       "604 2018-04-23  137.779999  138.160004  136.809998  137.449997  136.219604   \n",
       "605 2018-04-24  138.100006  138.190002  134.860001  135.800003  134.584366   \n",
       "606 2018-04-25  135.770004  136.250000  134.610001  135.949997  134.733032   \n",
       "607 2018-04-26  136.520004  137.679993  136.250000  137.240005  136.011490   \n",
       "608 2018-04-27  137.539993  137.740005  136.800003  137.330002  136.100677   \n",
       "\n",
       "      volume  month      est_N5  \n",
       "604  2033700      4  136.930182  \n",
       "605  3053500      4  135.601195  \n",
       "606  2275400      4  134.050198  \n",
       "607  1284600      4  133.751889  \n",
       "608  1133600      4  134.962961  "
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "est_list = get_preds_lin_reg(df, 'adj_close', N_opt, 0, num_train+num_cv)\n",
    "test['est' + '_N' + str(N_opt)] = est_list\n",
    "print(\"RMSE = %0.3f\" % math.sqrt(mean_squared_error(est_list, test['adj_close'])))\n",
    "print(\"R2 = %0.3f\" % r2_score(test['adj_close'], est_list))\n",
    "print(\"MAPE = %0.3f%%\" % get_mape(test['adj_close'], est_list))\n",
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1b81f7b8>"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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h2lZFxQ40zc2BA88CYDIl1lpOD+ZO/MPb663AYLBhsaTjcrVyZq6iAkJWBarN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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1bebf550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "\n",
    "ax = train.plot(x='date', y='adj_close', style='b-', grid=True)\n",
    "ax = cv.plot(x='date', y='adj_close', style='y-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='adj_close', style='g-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='est_N5', style='r-', grid=True, ax=ax)\n",
    "ax.legend(['train', 'dev', 'test', 'predictions with N_opt=5'])\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1a1d190128>"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9PXnvvffiveePP/6gdOnSVKhQgWeffTbbdc8LIURW5prZBfjH8PKCkiXh9Gko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KytW2JmZmbWATriSF5ETAQ0m1V2nIvXuB/4dLPaZGZmZtbNOuVInpmZmZk1kYs8MzMzsxpykWdm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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1cb6fba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "\n",
    "ax = train.plot(x='date', y='adj_close', style='bx-', grid=True)\n",
    "ax = cv.plot(x='date', y='adj_close', style='yx-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='adj_close', style='gx-', grid=True, ax=ax)\n",
    "ax = test.plot(x='date', y='est_N5', style='rx-', grid=True, ax=ax)\n",
    "ax.legend(['train', 'dev', 'test', 'predictions with N_opt=5'])\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")\n",
    "ax.set_xlim([date(2018, 6, 1), date(2018, 7, 31)])\n",
    "ax.set_ylim([135, 150])\n",
    "ax.set_title('Zoom in to test set')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(130, 155)"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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KYpobFRZCiGIrMlIL3ry9tdfDh4OdnTZnrEMHbtavn7/1e5xsbEV28vpJPMp4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k61Ol2VUjJTaOfWjq6WNqRbSgD4cPOHfLL1E2YOm8nQjkPr78VQK0FsPry5fFkvHx/1sWzY2hpi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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1bf697b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot adjusted close over time, only for test set\n",
    "rcParams['figure.figsize'] = 10, 8 # width 10, height 8\n",
    "matplotlib.rcParams.update({'font.size': 14})\n",
    "\n",
    "ax = test.plot(x='date', y='adj_close', style='gx-', grid=True)\n",
    "ax = test.plot(x='date', y='est_N5', style='rx-', grid=True, ax=ax)\n",
    "ax.legend(['test', 'predictions using linear regression'], loc='upper left')\n",
    "ax.set_xlabel(\"date\")\n",
    "ax.set_ylabel(\"USD\")\n",
    "ax.set_xlim([date(2018, 4, 23), date(2018, 11, 23)])\n",
    "ax.set_ylim([130, 155])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Save as csv\n",
    "test_lin_reg = test\n",
    "test_lin_reg.to_csv(\"./out/test_lin_reg.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Findings\n",
    "* On the dev set, the lowest RMSE is 1.2 which is achieved using N=1, ie. using value on day t-1 to predict value on day t\n",
    "* On the dev set, the next lowest RMSE is 1.36 which is achieved using N=5, ie. using values from days t-5 to t-1 to predict value on day t\n",
    "* We will use N_opt=5 in this work since our aim here is to use linear regression\n",
    "* On the test set, the RMSE is 1.42 and MAPE is 0.707% using N_opt=5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
